Variation In Biomass Research Articles

Monitoring of sea surface temperature, chlorophyll, and turbidity in Tunisian waters from 2005 to 2020 using MODIS imagery and the Google Earth Engine

Time series ocean color data product facilitates the study of spatio-temporal variability of various physical parameters of water, which allows the monitoring of water quality, interannual variability in phytoplankton biomass, and seasonal representation at different latitudes.Its role in marine biogeochemistry, water quality distribution, and climate fluctuation is very crucial., However, the lack of in situ measurement induces poor management and knowledge of the dynamics of Tunisian coastal waters. Therefore, this study aims to develop a workflow to monitor Tunisian waters based on long-term spatial observations of sea surface temperature, chlorophyll, and turbidity observations.Long-term sea surface observations were automatically obtained by processing the daily Moderate-resolution Imaging Spectroradiometer (MODIS) Aqua data via the Google Earth Engine (GEE) platform from 2005 to 2020. The recorded average monthly and yearly trends are validated by point-based measurements from the Gulf of Gabes and a qualitative analysis based on the bibliographic synthesis of offshore measurement campaigns in Tunisian waters. The hottest years were 2006, 2007, and 2017 while the coldest ones (12–28 °C) were 2011, 2012, and 2016. The highest chlorophyll content (10 and 5 μg L-1) was observed in 2006, 2007, 2011, 2012, 2015, 2016, and 2019. In addition, Turbidity peaks ranging between 11 nephelometric turbidity units (NTU) and 5 NTU were identified during December and January of 2005 2008, and 2011. Moreover, seasonal cyclicity and high correlations between estimated parameters were observed. Overall, combining the Google Earth Engine tool with daily MODIS data was effective for the routine monitoring of water quality parameters that is fast, accurate, and important for Tunisian coast management.

The zooplankton adaptation patterns along turbidity gradient in shallow water reservoirs

Turbidity is a precursor of several biotic phenomena in aquatic ecosystems, including differentiation of the zooplankton ensemble. We tested the hypothesis that the turbidity gradient in shallow artificial reservoirs can control the biomass of the most evenly distributed, i.e. the best adapted, population of a zooplankton species. This species can be sequentially linked to other zooplankton taxa to indicate a particular turbidity gradient. We assumed that each of the three water turbidity classes: high turbidity (HT), moderate turbidity (MT) and low turbidity (LT) can be represented by the best adapted species that establishes relationships with other species. These networks can indicate adaptation to the higher and lower levels of turbidity in the class. Random forest classification and regression models were used. The classification of zooplankton adaptation showed that variation in copepod nauplii biomass best reflected the turbidity classifications. Patterns of species occurrence by Daphnia cucullata Sars, 1862, Difflugia spp. and Cephalodella spp. (LT), Keratella cochlearis (Gosse, 1851) (MT), and K. cochlearis and Filinia longiseta (Ehrenberg, 1834) (HT) were formed at successive levels of the network. The adaptation patterns in each of the three turbidity classes were based on an optimal set and sequence of zooplankton functional traits, the ability to satisfy food needs, and interspecific relationships. Random forest modelling supported a comprehensive interpretation of the results, innovatively expanding existing knowledge on the functioning of turbid water ecosystems.

Variation in microbial biomass and enzymatic activities in metal contaminated soils during storage at low temperature (4°C)

ABSTRACT Microbial response to soil storage at low temperature in limed and unlimed samples has not been investigated. For this study, soil samples were kept at 4°C for six weeks. Soil microbial biomass was determined using phospholipid fatty acid analysis (PLFA). Nine enzymes were targeted including β-glucosidase (BG), cellobiohydrolase (CBH), β-N-acetylglucosaminidase (NAGase), aryl sulfatase (AS), acid phosphatase (AP), alkaline phosphatase (AlP), glycine aminopeptidase (GAP), leucine aminopeptidase (LAP), and peroxidase (PER). PLFA results revealed a significant increase in total microbial biomass in limed area compared to unlimed soil samples. Microbial biomass decreased during the first two weeks of storage and remained unchanged thereafter for both limed and unlimed samples. Analysis of microbial activities revealed that most enzymes inconsistently decreased over time during storage at 4°C. Activities of BG, CBH, NAGase, AlP, AS, GAP, LAP were significantly higher in limed compared to the unlimed samples. Overall, the levels of activities of most enzymes in limed soils decreased significantly after the second week of storage and remained unchanged thereafter. The reduction of enzyme activity in the unlimed soil samples varied over time, with some enzymes such as LAP increasing on the sixth week. PER activity decreased after two weeks and increased thereafter.

Assessment of understory vegetation in a plantation forest of the southeastern United States using terrestrial laser scanning

Forests of the southeastern United States are home to large timber industries with substantial contributions to global round wood production and paper products. Despite the success of plantations and the large timber industries in this area, pine growth remains constrained due to the competition between planted pine and the species in the understory. Moreover, effective control of this interspecies competition had shown a significant two- to four-times increase in stand productivity. Thus, this study aims to evaluate the use of laser scanning derived data from Terrestrial Laser Scanner (TLS) to assess understory vegetation biomass, as conventional methods utilizing optical imagery have yet to be effective in quantifying and mapping evergreen understory in the southeastern coastal forests of the United States. For this study, we utilized TLS to scan the entire forest profile within 60 sample plots of an operational loblolly pine plantation in Nassau County, Florida, and collected understory biomass data through destructive sampling. We compared three TLS-based volume estimation methods for predicting understory biomass and applied the Adaptive Least Absolute Shrinkage and Selection Operator (ALASSO) regression method to derive an optimal model by integrating the most efficient volume estimation methods and other TLS-derived standard metrics. Our study identifies the 20th percentile of the echo height and a 3D volume metric based on mean height and understory cover as the most significant explanatory variables for the optimal model. The model exhibits high accuracy, with Adjusted R-squared (Adj. R2) of 0.80 and Root Mean Square Error (RMSE) of 234.8 g per square meter (g/m2). Additionally, the mean height and understory-based volume estimation method outperformed other methods, such as voxel count and three dimensional (3D) alpha hall-based method, with Adj. R2 of 0.79, 0.47, and 0.57, and RMSE values of 288, 448.6, and 413 g/m2, respectively, when used as a single variable in the model. The resulting model successfully predicted and quantified understory vegetation, showcasing TLS's potential to accurately capture biomass variation, particularly in evergreen-dominated pine plantation forests in the southeastern United States coastal regions. As a tool for monitoring understory, TLS can be used to aid plantation forest managers in identifying areas that require control measures for enhanced management practices.

Basin-scale variability in phytoplankton size-abundance spectra across the Atlantic Ocean

Phytoplankton size structure, a major determinant of trophic structure and biogeochemical functioning in pelagic ecosystems, can be described by the slope of the size-abundance spectrum (SAS). Previous observational studies reporting spatio-temporal changes in phytoplankton SAS slope have focused on particular open-ocean or coastal environments. Therefore, the overall variability in phytoplankton SAS slope still has not been investigated over wide ranges of biomass and productivity including both oligotrophic open-ocean regions and productive coastal waters. Here we present a multi-cruise overview of the basin-scale variability in phytoplankton biomass and SAS slope across the Atlantic Ocean, covering coastal, shelf, and oceanic environments over the 50°N-50°S latitude range. We find the inverse relationship between cell size and abundance to be pervasive across the studied regions, even in highly productive coastal waters. In oceanic regions, consistent latitudinal patterns are observed in the relationship between nutricline depth, phytoplankton biomass and SAS slope. There is a strong degree of covariation between SAS slope at the surface and at the base of the euphotic layer, indicating that geographical changes in phytoplankton size structure override vertical variability. A basin-scale relationship exists between increasing resource supply, enhanced phytoplankton biomass, and progressively less steep SAS slopes, reflecting increasing importance of large cells in more productive waters. However, the relationship between ecosystem productivity and both SAS slope and mean community cell size is saturating, which means there is no continuous trend towards ever increasing contribution by larger cells. Similar phytoplankton size structures, with a biomass dominance by the 2–20 μm size class, are found in both moderately and highly eutrophic waters. Our results provide an observational benchmark for testing the predictions of size-based plankton models and for assessing future, climate-related shifts in phytoplankton size structure in both coastal and oceanic regions of the Atlantic Ocean.

Influence of nitrogen addition on the functional diversity and biomass of fine roots in warm-temperate and subtropical forests

Functional diversity strengthens species diversity and ecosystem function relationships; however, in the case of mixed forests, the relationship between fine root biomass and functional diversity is not completely understood. In this study, we compared fine root biomass and functional diversity of vegetation in response to canopy and understory nitrogen (N) addition rates of 0, 25, and 50 kg N ha−1 yr−1 in subtropical and warm-temperate forests. Canopy and understory N addition decreased the fine root biomass of the subtropical but increased the biomass of the warm-temperate forest during the growing season. The biomass and functional diversity of fine roots are more affected by N addition pattern than by rate. The functional richness index of fine roots was negatively correlated with fine root biomass at community level in the subtropical forest during the growing season, and NO3-N in the soil had the highest explanatory power for fine root biomass variation. Functional richness was positively correlated with fine root biomass at community level in the warm-temperate forest and had the highest explanatory power. In the warm-temperate forest, the synergistic increase in functional richness and fine root biomass promoted increases in nutrient uptake, whereas in the subtropical forest, either N restricted fine root growth or functional richness compensated for the reduction in fine root biomass. These findings indicate that the fine root biomass and functional diversity of subtropical and warm-temperate forests respond differentially to the addition of N.

Agronomic analysis of WaPOR applications: Confirming conservative biomass water productivity in inherent and climatological variance of WaPOR data outputs

CONTEXTImprovements in agricultural water productivity with constrained water resources are often regarded a prerequisite to meet food demands of a growing world population. The WaPOR data portal was launched to monitor biomass, evapotranspiration and biomass water productivity in Africa and the Near East using remote sensing technologies. The WaPOR database shows spatial pixel variation in biomass, suggesting scope to improve water productivity at field level. OBJECTIVEThe aim of this paper is to assess with regression analyses for different spatial and temporal scales whether spatial variability in biomass and evapotranspiration as revealed by WaPOR can be attributed to human influenceable factors, variations in local climate, or methodologically inherent inacuracies of the WaPOR data. METHODSVariation in biomass and evapotranspiration data was assessed through agronomic linear regression analyses, for two large-scale irrigated sugarcane estates in Ethiopia (Wonji) and Mozambique (Xinavane). RESULTS AND CONCLUSIONSIn these cases 82–94% of the variation in biomass and evapotranspiration is attributed to crop photosynthetic efficiency (very large influence), local climate (large influence) and irrigation technology (small influence). The remaining unexplained spatial variability is small (6–18%) and falls within an error range of +/− 9%. In conclusion, WaPOR performed very well by neatly reproducing the conservative relationship between biomass and evapotranspiration, which also means there is very limited scope to improve biomass water productivity through WaPOR monitoring. Further research is recommended on the magnitude of WaPOR accuracy and other sources that explain variations in biomass and evapotranspiration. SIGNIFCANCEApplicability of the WaPOR database to monitor biomass water productivity was assessed. Spatial variability in biomass and evapotranspiration data largely stemmed from photosynthesis and local climate, factors farmers and water managers can hardly influence.

Interannual and decadal variabilities of phytoplankton community in the Bering Sea and the Arctic Ocean: a case study of relationship with ENSO and Arctic Oscillation abnormity

We used molecular biomarkers (brassicasterol, dinosterol and C37 alkenones) measured from the surface sediments of the Bering Sea, the Chukchi Sea and the western Arctic Ocean in years of 1999 and 2010 to represent the groups of phytoplankton (diatoms, dinoflagellates and coccolithophores) and reconstruct the phytoplankton composition structure and biomass. The distribution of concentrations of three biomarkers were compatible to previous studies on measured phytoplankton, which showed that the phytoplankton biomass was most abundant in the Chukchi Sea, followed by the Bering Sea and the western Arctic Ocean, and diatoms were the dominant group. It suggests that molecular biomarkers are the suitable indicators of phytoplankton composition, structure and abundance. A record of biomarkers in a sediment core (NB01) collected at the Bering Sea in 2010 presented that the biomass of three phytoplankton groups increased in past 107 years, and their variation patterns were consistent. The synchronous increase of concentrations of phytoplankton biomarkers and cholesterol, a proxy of zooplankton biomass, implied that the primary production increased intensely in the last hundreds of years, corresponding to the trend of sea-ice melting as a result of global warming. Moreover, our results suggested that the combined effect of the anormal interannual changes of the El Niño-Southern Oscillation (ENSO) and the Arctic Oscillations (AO) played a key role in regulating the interannual and decadal variations of phytoplankton biomass and community composition, giving us an insight into the impact of atmospheric circulation on phytoplankton production and carbon flux in the Arctic seas.

Modeling stand biomass for Moso bamboo forests in Eastern China.

Stand biomass models can be used as basic decision-making tools in forest management planning. The Moso bamboo (Phyllostachys pubescens) forest, a major forest system in tropical and subtropical regions, represents a substantial carbon sink, slowing down the rise of greenhouse gas concentrations in the earth's atmosphere. Bamboo stand biomass models are important for the assessment of the contribution of carbon to the terrestrial ecosystem. We constructed a stand biomass model for Moso bamboo using destructively sampled data from 45 sample plots that were located across the Yixing state-owned farm in Jiangsu Province, China. Among several bamboo stand variables used as predictors in the stand biomass models, mean diameter at breast height (MDBH), mean height (MH), and canopy density (CD) of bamboo contributed significantly to the model. To increase the model's accuracy, we introduced the effects of bamboo forest block as a random effect into the model through mixed-effects modeling. The mixed-effects model described a large part of stand biomass variation (R2=0.6987), significantly higher than that of the ordinary least squares regression model (R2=0.5748). Our results show an increased bamboo stand biomass with increasing MH and CD, confirming our model's biological logic. The proposed stand biomass model may have important management implications; for example, it can be combined with other bamboo models to estimate bamboo canopy biomass, carbon sequestration, and bamboo biomass at different growth stages.

Fusarium oxysporum f. sp. lycopersici biomass variations under disease control regimes using Trichoderma and compost

A comprehensive understanding of population dynamics of pathogens and bioagents in plant rhizospheres is important for improving organic farming. Fusarium oxysporum f. sp. lycopersici (FOL30) causes Fusarium wilt of tomato. In this study, we compared biomass variations of FOL30 under different disease control regimes, using Trichoderma asperellum TA23 strain, compost, or their combination. Biomass variations of FOL30 and TA23 were observed for 13 weeks using quantitative real-time PCR. Separate applications of TA23, compost, and their combination all reduced FOL biomass when compared to experimental controls. Regression analyses of the qPCR data showed that FOL populations fitted curvilinear polynomial order 3 regression models (R2 = 0.87 to 0.95). Areas under the population dynamic curves (AUPDCs; log10 ng DNA week-1 g-1 soil) were: 43.8 from FOL30 alone, 36.6 from FOL30 plus TA23, 25.4 from FOL30 plus compost, and 25.5 from FOL30 plus TA23 plus compost. These results indicate that the individual applications of TA23 or compost, or their combination, decreased the FOL biomass. The negative correlation between TA23 and FOL30 populations showed that the compost and biocontrol agent reduced FOL pathogen populations. This study demonstrates that compost fortified with T. asperellum TA23 decreased FOL populations and reduced disease, and that their use is a promising strategy for managing Fusarium wilt of tomato in organic farming.

Functional diversity buffers biomass production across variable rainfall conditions through different processes above‐ versus below‐ground

Abstract Understanding precipitation controls on functional diversity is important in predicting how change in rainfall patterns will alter plant productivity in the future. Trait‐based approaches can provide predictive knowledge about how certain species will behave and interact with the community. However, how functional diversity relates to above‐ and below‐ground biomass production in variable rainfall conditions remains unclear. Here, we tested the role of mass ratio and niche complementarity hypotheses in shaping above‐ and below‐ground biomass–functional diversity relationships in seasonal drought. We implemented a fully crossed experiment that manipulated drought timing (fall dry, spring dry, consistent dry and ambient rainfall) and community composition (grass‐dominated, forb‐dominated and mixed grass–forb) in a California annual grassland. Plant communities with mixed functional groups showed higher above‐ and below‐ground biomass than either the grass‐ or forb‐dominant communities. We found divergent functional diversity–biomass relationships for above‐ and below‐ground biomass. Above‐ground biomass decreased with community weighted means (CWMs) of specific leaf area (SLA) and height, supporting the mass ratio hypothesis, which posits that dominant species with specific traits drive biomass production of the community. Below‐ground biomass showed no evidence of either mass ratio hypothesis or niche complementarity. While biomass was largely unaffected by the timing of drought in one season, we found community‐wide functional trait shifts in response to rainfall treatments. Above‐ground traits shifted to higher SLA in consistent dry compared to ambient. Below‐ground traits shifted to longer, finer and denser roots in fall and consistent dry, and shorter and coarser roots in spring dry. Functional diversity buffered biomass production by enabling shifts in above‐ and below‐ground functional traits across variable rainfall conditions. Read the free Plain Language Summary for this article on the Journal blog.

Demersal fish biomass declines with temperature across productive shelf seas

AbstractAimTheory predicts fish community biomass to decline with increasing temperature due to higher metabolic losses resulting in less efficient energy transfer in warm‐water food webs. However, whether these metabolic predictions explain observed macroecological patterns in fish community biomass is virtually unknown. Here, we test these predictions by examining the variation in demersal fish biomass across productive shelf regions.LocationTwenty one continental shelf regions in the North Atlantic and Northeast Pacific.Time Period1980–2015.Major Taxa StudiedMarine teleost fish and elasmobranchs.MethodsWe compiled high‐resolution bottom trawl survey data of fish biomass containing 166,000 unique tows and corrected biomass for differences in sampling area and trawl gear catchability. We examined whether relationships between net primary production and demersal fish community biomass are mediated by temperature, food‐web structure and the level of fishing exploitation, as well as the choice of spatial scale of the analysis. Subsequently, we examined if temperature explains regional changes in fish biomass over time under recent warming.ResultsWe find that biomass per km2 varies 40‐fold across regions and is highest in cold waters and areas with low fishing exploitation. We find no evidence that temperature change has impacted biomass within marine regions over the time period considered. The biomass variation is best explained by an elementary trophodynamic model that accounts for temperature‐dependent trophic efficiency.Main ConclusionsOur study supports the hypothesis that temperature is a main driver of large‐scale cross‐regional variation in fish community biomass. The cross‐regional pattern suggests that long‐term impacts of warming will be negative on biomass. These results provide an empirical basis for predicting future changes in fish community biomass and its associated services for human wellbeing that is food provisioning, under global climate change.

Biomass and diversity of epiphytic liverworts along environmental gradients in a cloud forest in Mexico

ABSTRACT Introduction Bryophytes can reach levels of coverage sufficient to influence key ecological processes; for example, their water retention capacity can supply an appreciable amount of humidity to forest ecosystems. The variation in biomass and diversity of epiphytic liverwort species in a Mexican cloud forest (CF) in the state of Hidalgo was estimated along elevation and latitude gradients, as was the relationship between epiphytic liverwort structural attributes and environmental factors. Methods Liverwort species were sampled in three municipalities with CF in Hidalgo State, at elevations of 1345–2019 m. In each municipality, two 0.1 ha plots were located at the two extremes of the gradient. For each of 10 trees per plot, three 10 × 10 cm areas of bark were selected as microplots, and from each microplot, samples of liverwort were obtained to determine structural data for the liverworts. Key results Species diversity was highest at the upper elevation level (1985–2001 m), and lowest at the lower elevation level (1345–1375 m). The highest dry and saturated weight values (15.20 g and 83.30 g, respectively) were found at lower elevations, and the lowest (11.78 g and 60.04 g, respectively) at high elevations. Conclusion Species diversity was positively related to elevation gradient, and species biomass decreased gradually with elevation. Beta diversity values were not associated with geographical distance between sites. Local factors, such as light input, available area, phorophyte species, humidity and temperature, may have more influence on the growth of epiphytic liverworts than elevation or geographical distance.

From simple metrics to cervid forage: Improving predictions of ericaceous shrub biomass

Common understory vegetation species such as the ericaceous shrubs bilberry (Vaccinium myrtillus), cowberry (V. vitis-idaea) and heather (Calluna vulgaris), are key forage plant species for moose and other large herbivores, as well as fulfilling many additional ecosystem functions and services. Here we developed models to predict above-ground biomass of these ericaceous species in coniferous forests, using data on their percentage cover, height, and different stand characteristics. We also built models to understand how the aforementioned variables affect the proportion of the shrubs commonly utilized as forage by large herbivores. We found that the percentage cover of shrubs was the most important explanatory variable when predicting above-ground biomass, explaining 51%, 47% and 71% of the variation (marginal R2) in bilberry, cowberry and heather biomass, respectively. By adding ramet height to the model with percentage cover, the variation explained increased to 77% for bilberry, 75% for cowberry and 87% for heather. The best outcome for candidate models was obtained by adding stand site index and spruce basal area to the model, improving the variation explained in bilberry to 83%, to 81% for cowberry, and 91% for heather. When modelling the proportion of the shrubs commonly utilized as forage by large herbivores, stand site index and spruce basal area often played important roles. Some of the best fitting models for forage biomass explained 51% of the variation in bilberry, 59% in cowberry and 30% in heather. Site location did not have a major role in improving the variability explained in either type of model, which indicated the applicability of the models regardless of study location. Our models therefore have a high potential to be implemented in forestry decision support systems. Their inclusion should provide better large-scale estimations of forage resources, aiding forest management, and thereby taking an important step forward to determine the ecosystem carrying capacity of large herbivores.

Efficient degradation of ciprofloxacin and erythromycin coupled to elevated lipid synthesis in Synechococcus sp. and Chroococcus sp.

The variations of cell density, photosynthesis activity, biomass, lipid productivity, ultra-structure and metabolomic profile of two non-toxic cyanobacterial species, Synechococcus sp. and Chroococcus sp., during the degradation of two frequently detected antibiotics, ciprofloxacin and erythromycin, were investigated through a 4-day exposure test at antibiotic exposure doses of 0.2–20.0 μg/L. Each target antibiotic induced hormetic effects on cell density and photosynthesis activity of each cyanobacterial species. The lipid productivity of Synechococcus sp. was elevated to 18.70 mg/L/d and 25.95 mg/L/d under exposure to ciprofloxacin and erythromycin, respectively. The lipid productivity of Chroococcus sp. was elevated to 26.25 mg/L/d and 22.85 mg/L/d by ciprofloxacin and erythromycin, respectively. The increase of cell weight or lipid content or both of them contributed to the elevation of lipid productivity. Increased number and size of lipid droplets were observed in cyanobacterial cells exposed to target antibiotics through transmission electron microscopy. Upregulation of monoacylglycerols and fatty acids were observed in cyanobacterial cells under antibiotic exposure through metabolomic analysis. Due to the cooperation of abiotic degradation, biosorption and biodegradation, Synechococcus sp. removed 48.72 %–64.71 % of ciprofloxacin and 43.22 %–82.43 % of erythromycin from the culture medium, and Chroococcus sp. removed 43.34 %–63.15 % of ciprofloxacin and 38.32 %–74.36 % of erythromycin. Several degradation products were identified for each antibiotic during the removal process by each cyanobacterial species. Results of this study demonstrated prospects for the utilization of non-toxic cyanobacteria in treating antibiotic-contaminated wastewater and meanwhile producing cyanobacterial biodiesel within a short culture period of 4 days.

Spatiotemporal Variability of Alpine Meadow Aboveground Biomass and Sustainable Grazing in Light of Climate Warming

Understanding spatiotemporal variability of aboveground biomass (AGB) in alpine grassland ecosystems is required to better formulate sustainable grazing strategies, especially in climate-sensitive areas such as the Qinghai-Tibet Plateau. Drawing from recent modeling results, we analyzed spatial variability in grassland AGB over seasonal and annual timescales. Theoretical livestock carrying capacity (LCC) was predicted in relation to projected warming and simulated pika disturbance. We found that elevation and slope were key determinants of the distribution of AGB and its change. Although grasses and shrubs occupied an equivalent area, the latter generated approximately double the amount of total biomass, but the former generated slightly more available biomass. Although pika habitat extended over 45.3% of the study area, the impacts of pika only reduced the total available AGB (AGBV) by < 0.07%. The actual LCC (2.16 SU · ha−1 [sheep unit per hectare]) of the study area was lower than the theoretical LCC (2.77−2.96 SU · ha−1). Under climate warming scenarios of 1.0°C, 1.5°C, and 2.0°C, the actual LCC can be increased by 0.82-1.25, 0.99-1.53, and 0.77−1.23 SU · ha−1, respectively. Although systematic climate warming increased AGB, impacts were especially marked at lower elevations and on north-facing slopes because of higher soil water availability. Results highlight that rather than implementing LCC in a static manner in light of climate warming, deeper understanding of biomass availability and the combined effects of climate change and topographic heterogeneity is required to support better management of grasslands.

Woody plant diversity and aboveground carbon stock of Dipterocarpus chartaceus dominant forests in Binh Chau-Phuoc Buu Nature Reserve, South Vietnam

Abstract. Hop NV, Quy NV, Lam NV, Trong PT, Thinh PC. 2023. Woody plant diversity and aboveground carbon stock of Dipterocarpus chartaceus dominant forests in Binh Chau-Phuoc Buu Nature Reserve, South Vietnam. Asian J For: 114-124. The dominant forest of Dipterocarpus chartaceus Symington in Binh Chau-Phuoc Buu Nature Reserve, South Vietnam, has an important ecological role and high conservation value relevant to climate change by storing large amounts of CO2 from the atmosphere. This study assesses the diversity of woody plants and estimates biomass and carbon stocks in different forest states. The study used a typical sample plot setting method was used. Trees with a Diameter at Breast Height (DBH) &gt; 6 cm were measured, and species were identified in 9 sample plots of 50m x 20m in the very poor, poor, and medium forests. A total of 640 tree individuals belonging to 45 species, 34 genera, and 25 families were recorded. The most species-rich family was represented by Dipterocarpaceae (7 species). A total of 15 threatened species (33.33%) belonging to 11 genera from 8 families were listed in the Vietnam Red Data Book (2007) and IUCN Red List (2022). The Margalef (d), Shannon-Wiener (H'), Simpson (Cd), and Sorensen Index (SI) were analyzed for tree species. The study illustrated that medium forests had the highest diversity, followed by poor forests, and the lowest belonged to very poor forests. The ability to accumulate biomass and aboveground carbon stocks varied widely from 48.15 t/ha-196.15 t/ha and 24.07 Ct/ha-98.42 Ct/ha. The medium forest had the highest total carbon stock, followed by the very poor forest and the lowest poor forest. The study provides an essential database for strategies and plans for conserving plant biodiversity and improving the power of CO2 accumulation to adapt to climate change.

Determination of the Best Performing Sri Lankan Maize Accessions Based on the Photosynthetic, Biomass and Yield Traits

Maize (Zea mays L.) is one of the most widely cultivated cereal crops throughout the world and is extensively grown in Sri Lanka. Information on the photosynthetic, biomass and grain yield of local maize accessions are useful for plant breeding programs. However, due to the scarcity of such information, this study aimed to investigate the potentials of maize accessions to select the best performers utilizing the rank summation and selection index criteria. As the first step, the seeds from 14 maize accessions along with two varieties viz; Pacific-999 and Bhadra (control) were established in the field. The leaf-level photosynthetic and chlorophyll fluorescence traits were analyzed, while biomass and yield traits were obtained at harvest, by employing standard techniques. Our findings revealed that traits related to growth, photosynthesis, and biomass showed greater variations among the maize accessions tested. The number of days taken to 50% flowering (44d-60d), photosynthetic rates (19.7-30.45 μmol CO2 m−2 s−1), transpiration rates (2.45-4.52 mmol H2O m−2 s−1), water use efficiency (5.69-8.13 μmol CO2 mmol H2O-1), and maximum quantum yield (0.68-0.73) among the tested accessions. Additionally, the variations in biomass (111.0-459 g/plant) and final cob yield (38-232 g/cob) were also seen among the maize accessions. According to rank summation index analysis, the maize accessions SEU2, SEU16, SEU15, SEU9 and SEU10 were superior in terms of photosynthetic rates, biomass and yield compared exhibiting with the lowest RSI values of 71, 100, 101, 103 and 117, respectively, than the cv. Bhadra. Therefore, future crop development programs can make use of these five potential maize accessions identified through this study.

The Correlation between Genotype Richness of Submerged Macrophytes and Periphyton Biomass: A Mesocosm Study Based on Five Dominant Submerged Macrophytes from Yangtze River

Submerged macrophyte and periphyton are main primary producers which strongly interact with each other in clear water shallow lakes. In this study, the effects of genetic variation of the macrophyte species on periphyton biomass were studied in five submerged species. A two-year mesocosm study was conducted with four levels of genetic diversity (1, 4, 8 and 16 genotypes) for each submerged macrophyte, including 1600 individuals and 320 boxes in 20 mesocosms. Of the five submerged species, only Vallisneria spinulosa showed a positive correlation between its levels of genotype richness and the periphyton biomass. The correlation between genetic distance of genotypes and periphyton biomass was tested, which varied with the difference of seasons and species. In summary, we found that in freshwater mesocosms, the genetic diversity of submerged macrophytes may play a role in regulating the periphyton biomass, but the interaction between genetic diversity of macrophytes and periphyton biomass was not straightforward. This study will provide new insights into the interaction dynamics between the two primary producers in shallow lakes.

Ancient and modern wheat varieties: A trade‐off between soil CO2 emissions and grain yield?

AbstractIntroductionHumanity is facing two great challenges: producing enough food for a growing population and mitigating greenhouse gas emissions. In this study, we investigated the choice of specific wheat varieties to improve carbon storage in soil while producing enough grain to assure food security. We hypothesize that ancient wheat varieties could store more carbon than modern ones, due to a likely bigger and deeper root system or to more recalcitrant root organic matter.Materials and MethodsWe conducted a field experiment with four modern and four ancient wheat varieties, on four different sites with contrasted soil properties. Root morphology was assessed by image analysis and potential CO2 emissions by incubation for 60 days. Since in situ carbon storage differences between ancient and modern varieties were expected to be weak and not cumulated due to rotation, we estimated expected CO2 emissions from root biomass and potential CO2 emissions. The grain yield was also measured.ResultsThe breeding type (ancient vs. modern varieties) affected root length in two of our four sites, with longer roots for ancient varieties, but it did not affect other root traits such as biomass. The breeding type also affected CO2 emissions, with higher measured CO2 emissions for modern than ancient varieties in Arenic Cambisol conditions (Morvan), and higher estimated (considering root biomass variations) CO2 emissions for modern varieties in Rendzic Leptosol conditions (Saint Romain). Root traits and estimated CO2 emissions were also dependent on the soil properties of the different sites. We did not find any significant differences in grain yield between ancient and modern varieties.ConclusionA possible trade‐off between carbon storage and grain production was expected, but our results suggest that some types of soil can support both high grain yield and C storage, especially those with an important depth, a neutral pH and a fine texture.